def test_forces_observable(self):
fname = os.path.join(self.dir, "test_observables_particle_forces.h5")
context = Context()
context.box_size = [13., 13., 13.]
context.particle_types.add("A", .1)
sim = Simulation("CPU", context)
sim.add_particle("A", common.Vec(0, 0, 0))
# every time step, add one particle
sim.register_observable_n_particles(
1, ["A"],
lambda n: sim.add_particle("A", common.Vec(1.5, 2.5, 3.5)))
handle = sim.register_observable_forces(1, [])
n_timesteps = 19
with closing(io.File.create(fname)) as f:
handle.enable_write_to_file(f, u"forces", int(3))
sim.run(n_timesteps, 1.)
handle.flush()
with h5py.File(fname, "r") as f2:
data = f2["readdy/observables/forces/data"][:]
time_series = f2["readdy/observables/forces/time"]
np.testing.assert_equal(len(data), n_timesteps + 1)
np.testing.assert_equal(time_series,
np.array(range(0, n_timesteps + 1)))
for t, forces in enumerate(data):
# we begin with two particles
np.testing.assert_equal(len(forces), t + 2)
np.testing.assert_equal(forces[0]["x"], 0)
np.testing.assert_equal(forces[0]["y"], 0)
np.testing.assert_equal(forces[0]["z"], 0)
for i in range(1, len(forces)):
np.testing.assert_equal(forces[i]["x"], 0)
np.testing.assert_equal(forces[i]["y"], 0)
np.testing.assert_equal(forces[i]["z"], 0)
def test_histogram_along_axis_observable(self):
fname = os.path.join(self.dir, "test_observables_hist_along_axis.h5")
simulation = Simulation("SingleCPU")
box_size = [10.,10.,10.]
simulation.context.kbt = 2
simulation.context.pbc = [True, True, True]
simulation.context.box_size = box_size
simulation.context.particle_types.add("A", .2)
simulation.context.particle_types.add("B", .2)
simulation.context.potentials.add_harmonic_repulsion("A", "B", 10, 2.)
simulation.add_particle("A", common.Vec(-2.5, 0, 0))
simulation.add_particle("B", common.Vec(0, 0, 0))
bin_borders = np.arange(0, 5, .01)
n_time_steps = 50
callback_hist = []
def hist_callback(hist):
callback_hist.append(hist)
handle = simulation.register_observable_histogram_along_axis(2, bin_borders, 0, ["A", "B"], hist_callback)
with closing(io.File.create(fname)) as f:
handle.enable_write_to_file(f, u"hist_along_x_axis", int(3))
simulation.run(n_time_steps, 0.02)
handle.flush()
with h5py.File(fname, "r") as f2:
histogram = f2["readdy/observables/hist_along_x_axis/data"][:]
time_series = f2["readdy/observables/hist_along_x_axis/time"]
np.testing.assert_equal(time_series, np.array(range(0, n_time_steps+1))[::2])
for t in range(n_time_steps // 2):
np.testing.assert_equal(histogram[t], np.array(callback_hist[t]))
def chain_decay(self, kernel):
sim = Simulation(kernel)
sim.context.box_size = [10., 10., 10.]
sim.context.topologies.add_type("TA")
np.testing.assert_equal(sim.kernel_supports_topologies(), True)
sim.context.particle_types.add("B", 1.0, ParticleTypeFlavor.NORMAL)
sim.context.particle_types.add("Topology A", 1.0, ParticleTypeFlavor.TOPOLOGY)
sim.context.topologies.configure_bond_potential("Topology A", "Topology A", BondedPotentialConfiguration(10, 10, "harmonic"))
n_elements = 50.
particles = [sim.create_topology_particle("Topology A", common.Vec(-5. + i * 10. / n_elements, 0, 0))
for i in range(int(n_elements))]
topology = sim.add_topology("TA", particles)
for i in range(int(n_elements - 1)):
topology.get_graph().add_edge(i, i + 1)
sim.context.topologies.add_structural_reaction("TA", self._get_decay_reaction())
sim.context.topologies.add_structural_reaction("TA", self._get_split_reaction())
# h = sim.register_observable_n_particles(1, [], lambda x: print("n particles=%s" % x))
np.testing.assert_equal(1, len(sim.current_topologies))
sim.run(500, 1.)
np.testing.assert_equal(0, len(sim.current_topologies))
def test_virial_observable_CPU(self):
fname = os.path.join(self.dir, "test_observables_virial.h5")
sim = Simulation("CPU")
sim.context.box_size = [13., 13., 13.]
sim.context.particle_types.add("A", .1)
sim.context.potentials.add_harmonic_repulsion("A", "A", 10., .5)
for _ in range(10000):
pos = common.Vec(*(13*np.random.random(size=3)-.5*13))
sim.add_particle("A", pos)
virials = []
def virial_callback(virial):
virials.append(np.ndarray((3,3), buffer=virial))
handle = sim.register_observable_virial(1, virial_callback)
with closing(io.File.create(fname)) as f:
handle.enable_write_to_file(f, u"virial", int(3))
sim.run(10, .1)
handle.flush()
with h5py.File(fname, "r") as f2:
h5virials = f2["readdy/observables/virial/data"]
for v, v2 in zip(virials, h5virials):
np.testing.assert_almost_equal(v, v2)
def test_particle_positions_observable(self):
fname = os.path.join(self.dir, "test_observables_particle_positions.h5")
sim = Simulation("SingleCPU")
sim.context.box_size = [13., 13., 13.]
sim.context.particle_types.add("A", .1)
sim.add_particle("A", common.Vec(0, 0, 0))
# every time step, add one particle
sim.register_observable_n_particles(1, ["A"], lambda n: sim.add_particle("A", common.Vec(1.5, 2.5, 3.5)))
handle = sim.register_observable_particle_positions(1, [])
n_timesteps = 19
with closing(io.File.create(fname)) as f:
handle.enable_write_to_file(f, u"particle_positions", int(3))
sim.run(n_timesteps, 0)
handle.flush()
with h5py.File(fname, "r") as f2:
data = f2["readdy/observables/particle_positions/data"][:]
np.testing.assert_equal(len(data), n_timesteps + 1)
for t, positions in enumerate(data):
# we begin with two particles
np.testing.assert_equal(len(positions), t + 2)
np.testing.assert_equal(positions[0]["x"], 0)
np.testing.assert_equal(positions[0]["y"], 0)
np.testing.assert_equal(positions[0]["z"], 0)
for i in range(1, len(positions)):
np.testing.assert_equal(positions[i]["x"], 1.5)
np.testing.assert_equal(positions[i]["y"], 2.5)
np.testing.assert_equal(positions[i]["z"], 3.5)
class TestInternalSimulationModule(ReaDDyTestCase):
def setUp(self):
super().setUp()
self.kernel_provider = KernelProvider.get()
self.kernel_provider.load_from_dir(platform_utils.get_readdy_plugin_dir())
self.simulation = Simulation()
def py_harmonic_repulsion_energy(self, x_ij):
dist = x_ij * x_ij
# if dist < sqrt(25): return energy with force constant 1
if dist < 25:
return (np.sqrt(dist) - 5) ** 2
else:
return 0
def py_harmonic_repulsion_force(self, x_ij):
dist = x_ij * x_ij
if dist < 25:
dist = np.sqrt(dist)
return (2 * (dist - 5) / dist) * x_ij
else:
return Vec(0, 0, 0)
def test_properties(self):
if not self.simulation.is_kernel_selected():
self.simulation.set_kernel('SingleCPU')
np.testing.assert_equal(self.simulation.is_kernel_selected(), True)
np.testing.assert_equal(self.simulation.get_selected_kernel_type(), "SingleCPU")
self.simulation.kbt = 5.0
np.testing.assert_equal(self.simulation.kbt, 5.0)
self.simulation.periodic_boundary = [True, False, True]
np.testing.assert_equal(self.simulation.periodic_boundary, (True, False, True))
self.simulation.box_size = Vec(1, 3.6, 7)
np.testing.assert_equal(self.simulation.box_size, Vec(1, 3.6, 7))
def py_position_observable_callback(self, positions):
_vec_sum = Vec(0, 0, 0)
for v in positions:
_vec_sum += v
mean = _vec_sum / float(len(positions))
print("mean=%s" % mean)
def test_potentials(self):
if not self.simulation.is_kernel_selected():
self.simulation.set_kernel("SingleCPU")
ida = self.simulation.register_particle_type("ParticleTypeA", 1.0)
idb = self.simulation.register_particle_type("ParticleTypeB", 3.0)
self.simulation.register_particle_type("ParticleTypeA_internal", 1.0)
self.simulation.register_particle_type("ParticleTypeB_internal", 3.0)
pot = Pot2(ida, idb, self.py_harmonic_repulsion_energy,
self.py_harmonic_repulsion_force)
self.simulation.register_potential_order_2(pot)
self.simulation.register_potential_harmonic_repulsion("ParticleTypeA_internal", "ParticleTypeB_internal", 1.0, 2.0)
self.simulation.add_particle("ParticleTypeA", Vec(0, 0, 0))
self.simulation.add_particle("ParticleTypeB", Vec(0.4, 0.4, 0.4))
self.simulation.run(100, 1)
def test_n_particles_observable(self):
common.set_logging_level("warn")
fname = os.path.join(self.dir, "test_observables_n_particles.h5")
simulation = Simulation()
simulation.set_kernel("SingleCPU")
box_size = common.Vec(10, 10, 10)
simulation.kbt = 2
simulation.periodic_boundary = [True, True, True]
simulation.box_size = box_size
simulation.register_particle_type("A", .2, 1.)
simulation.register_particle_type("B", .2, 1.)
simulation.add_particle("A", common.Vec(-2.5, 0, 0))
simulation.add_particle("B", common.Vec(0, 0, 0))
n_time_steps = 50
callback_n_particles_a_b = []
callback_n_particles_all = []
def callback_ab(value):
callback_n_particles_a_b.append(value)
simulation.add_particle("A", common.Vec(-1, -1, -1))
def callback_all(hist):
callback_n_particles_all.append(hist)
simulation.add_particle("A", common.Vec(-1, -1, -1))
simulation.add_particle("B", common.Vec(-1, -1, -1))
handle_a_b_particles = simulation.register_observable_n_particles(
1, ["A", "B"], callback_ab)
handle_all = simulation.register_observable_n_particles(
1, [], callback_all)
with closing(
io.File(fname, io.FileAction.CREATE,
io.FileFlag.OVERWRITE)) as f:
handle_a_b_particles.enable_write_to_file(f, u"n_a_b_particles",
int(3))
handle_all.enable_write_to_file(f, u"n_particles", int(5))
simulation.run(n_time_steps, 0.02)
handle_all.flush()
handle_a_b_particles.flush()
with h5py.File(fname, "r") as f2:
n_a_b_particles = f2["readdy/observables/n_a_b_particles/data"][:]
n_particles = f2["readdy/observables/n_particles/data"][:]
time_series = f2["readdy/observables/n_a_b_particles/time"]
np.testing.assert_equal(time_series,
np.array(range(0, n_time_steps + 1)))
for t in range(n_time_steps):
np.testing.assert_equal(n_a_b_particles[t][0],
callback_n_particles_a_b[t][0])
np.testing.assert_equal(n_a_b_particles[t][1],
callback_n_particles_a_b[t][1])
np.testing.assert_equal(n_particles[t][0],
callback_n_particles_all[t][0])
def test_sanity(self):
context = Context()
context.box_size = [10., 10., 10.]
context.topologies.add_type("TA")
context.particle_types.add("T",
1.0,
flavor=ParticleTypeFlavor.TOPOLOGY)
context.topologies.configure_bond_potential(
"T", "T", BondedPotentialConfiguration(10., 11., "harmonic"))
sim = Simulation("SingleCPU", context)
np.testing.assert_equal(sim.kernel_supports_topologies(), True)
particles = [
sim.create_topology_particle("T", common.Vec(x, 0, 0))
for x in range(4)
]
top = sim.add_topology("TA", particles)
graph = top.graph
graph.add_edge(0, 1)
graph.add_edge(1, 2)
graph.add_edge(2, 3)
np.testing.assert_equal(len(graph.get_vertices()), 4)
for v in graph.vertices:
if v.particle_index == 0:
np.testing.assert_equal(top.position_of_vertex(v),
common.Vec(0, 0, 0))
np.testing.assert_equal(len(v.neighbors()), 1)
np.testing.assert_equal(
1 in [vv.get().particle_index for vv in v], True)
if v.particle_index == 1:
np.testing.assert_equal(top.position_of_vertex(v),
common.Vec(1, 0, 0))
np.testing.assert_equal(len(v.neighbors()), 2)
np.testing.assert_equal(
0 in [vv.get().particle_index for vv in v], True)
np.testing.assert_equal(
2 in [vv.get().particle_index for vv in v], True)
if v.particle_index == 2:
np.testing.assert_equal(top.position_of_vertex(v),
common.Vec(2, 0, 0))
np.testing.assert_equal(len(v.neighbors()), 2)
np.testing.assert_equal(
1 in [vv.get().particle_index for vv in v], True)
np.testing.assert_equal(
3 in [vv.get().particle_index for vv in v], True)
if v.particle_index == 3:
np.testing.assert_equal(top.position_of_vertex(v),
common.Vec(3, 0, 0))
np.testing.assert_equal(len(v.neighbors()), 1)
np.testing.assert_equal(
2 in [vv.get().particle_index for vv in v], True)
top.configure()
sim.run(0, 1)
def test_n_particles_observable(self):
fname = os.path.join(self.dir, "test_observables_n_particles.h5")
context = Context()
box_size = [10., 10., 10.]
context.kbt = 2
context.pbc = [True, True, True]
context.box_size = box_size
context.particle_types.add("A", .2)
context.particle_types.add("B", .2)
simulation = Simulation("SingleCPU", context)
simulation.add_particle("A", common.Vec(-2.5, 0, 0))
simulation.add_particle("B", common.Vec(0, 0, 0))
n_time_steps = 50
callback_n_particles_a_b = []
callback_n_particles_all = []
def callback_ab(value):
callback_n_particles_a_b.append(value)
simulation.add_particle("A", common.Vec(-1, -1, -1))
def callback_all(hist):
callback_n_particles_all.append(hist)
simulation.add_particle("A", common.Vec(-1, -1, -1))
simulation.add_particle("B", common.Vec(-1, -1, -1))
handle_a_b_particles = simulation.register_observable_n_particles(
1, ["A", "B"], callback_ab)
handle_all = simulation.register_observable_n_particles(
1, [], callback_all)
with closing(io.File.create(fname)) as f:
handle_a_b_particles.enable_write_to_file(f, u"n_a_b_particles",
int(3))
handle_all.enable_write_to_file(f, u"n_particles", int(5))
simulation.run(n_time_steps, 0.02)
handle_all.flush()
handle_a_b_particles.flush()
with h5py.File(fname, "r") as f2:
n_a_b_particles = f2["readdy/observables/n_a_b_particles/data"][:]
n_particles = f2["readdy/observables/n_particles/data"][:]
time_series = f2["readdy/observables/n_a_b_particles/time"]
np.testing.assert_equal(time_series,
np.array(range(0, n_time_steps + 1)))
for t in range(n_time_steps):
np.testing.assert_equal(n_a_b_particles[t][0],
callback_n_particles_a_b[t][0])
np.testing.assert_equal(n_a_b_particles[t][1],
callback_n_particles_a_b[t][1])
np.testing.assert_equal(n_particles[t][0],
callback_n_particles_all[t][0])
def test_radial_distribution_observable(self):
common.set_logging_level("warn")
fname = os.path.join(self.dir,
"test_observables_radial_distribution.h5")
simulation = Simulation()
simulation.set_kernel("SingleCPU")
box_size = common.Vec(10, 10, 10)
simulation.kbt = 2
simulation.periodic_boundary = [True, True, True]
simulation.box_size = box_size
simulation.register_particle_type("A", .2, 1.)
simulation.register_particle_type("B", .2, 1.)
simulation.register_potential_harmonic_repulsion("A", "B", 10)
simulation.add_particle("A", common.Vec(-2.5, 0, 0))
simulation.add_particle("B", common.Vec(0, 0, 0))
bin_borders = np.arange(0, 5, .01)
density = 1. / (box_size[0] * box_size[1] * box_size[2])
n_time_steps = 50
callback_centers = []
callback_rdf = []
def rdf_callback(pair):
callback_centers.append(pair[0])
callback_rdf.append(pair[1])
handle = simulation.register_observable_radial_distribution(
1, bin_borders, ["A"], ["B"], density, rdf_callback)
with closing(
io.File(fname, io.FileAction.CREATE,
io.FileFlag.OVERWRITE)) as f:
handle.enable_write_to_file(f, u"radial_distribution", int(3))
simulation.run(n_time_steps, 0.02)
handle.flush()
with h5py.File(fname, "r") as f2:
bin_centers = f2[
"readdy/observables/radial_distribution/bin_centers"][:]
distribution = f2[
"readdy/observables/radial_distribution/distribution"][:]
for t in range(n_time_steps):
np.testing.assert_equal(bin_centers,
np.array(callback_centers[t]))
np.testing.assert_equal(distribution[t],
np.array(callback_rdf[t]))
def test_n_particles_observable(self):
fname = os.path.join(self.dir, "test_observables_n_particles.h5")
simulation = Simulation()
simulation.set_kernel("SingleCPU")
box_size = common.Vec(10, 10, 10)
simulation.kbt = 2
simulation.periodic_boundary = [True, True, True]
simulation.box_size = box_size
simulation.register_particle_type("A", .2)
simulation.register_particle_type("B", .2)
simulation.add_particle("A", common.Vec(-2.5, 0, 0))
simulation.add_particle("B", common.Vec(0, 0, 0))
n_time_steps = 50
callback_n_particles_a_b = []
callback_n_particles_all = []
def callback_ab(value):
callback_n_particles_a_b.append(value)
simulation.add_particle("A", common.Vec(-1, -1, -1))
def callback_all(hist):
callback_n_particles_all.append(hist)
simulation.add_particle("A", common.Vec(-1, -1, -1))
simulation.add_particle("B", common.Vec(-1, -1, -1))
handle_a_b_particles = simulation.register_observable_n_particles(1, ["A", "B"], callback_ab)
handle_all = simulation.register_observable_n_particles(1, [], callback_all)
with closing(io.File.create(fname)) as f:
handle_a_b_particles.enable_write_to_file(f, u"n_a_b_particles", int(3))
handle_all.enable_write_to_file(f, u"n_particles", int(5))
simulation.run(n_time_steps, 0.02)
handle_all.flush()
handle_a_b_particles.flush()
with h5py.File(fname, "r") as f2:
n_a_b_particles = f2["readdy/observables/n_a_b_particles/data"][:]
n_particles = f2["readdy/observables/n_particles/data"][:]
time_series = f2["readdy/observables/n_a_b_particles/time"]
np.testing.assert_equal(time_series, np.array(range(0, n_time_steps+1)))
for t in range(n_time_steps):
np.testing.assert_equal(n_a_b_particles[t][0], callback_n_particles_a_b[t][0])
np.testing.assert_equal(n_a_b_particles[t][1], callback_n_particles_a_b[t][1])
np.testing.assert_equal(n_particles[t][0], callback_n_particles_all[t][0])
def test_radial_distribution_observable(self):
fname = os.path.join(self.dir,
"test_observables_radial_distribution.h5")
context = Context()
context.kbt = 2
context.pbc = [True, True, True]
box_size = [10., 10., 10.]
context.box_size = box_size
context.particle_types.add("A", .2)
context.particle_types.add("B", .2)
context.potentials.add_harmonic_repulsion("A", "B", 10, 2.)
simulation = Simulation("SingleCPU", context)
simulation.add_particle("A", common.Vec(-2.5, 0, 0))
simulation.add_particle("B", common.Vec(0, 0, 0))
bin_borders = np.arange(0, 5, .01)
density = 1. / (box_size[0] * box_size[1] * box_size[2])
n_time_steps = 50
callback_centers = []
callback_rdf = []
def rdf_callback(pair):
callback_centers.append(pair[0])
callback_rdf.append(pair[1])
handle = simulation.register_observable_radial_distribution(
1, bin_borders, ["A"], ["B"], density, rdf_callback)
with closing(io.File.create(fname)) as f:
handle.enable_write_to_file(f, u"radial_distribution", int(3))
simulation.run(n_time_steps, 0.02)
handle.flush()
with h5py.File(fname, "r") as f2:
bin_centers = f2[
"readdy/observables/radial_distribution/bin_centers"][:]
distribution = f2[
"readdy/observables/radial_distribution/distribution"][:]
for t in range(n_time_steps):
np.testing.assert_equal(bin_centers,
np.array(callback_centers[t]))
np.testing.assert_equal(distribution[t],
np.array(callback_rdf[t]))
def test_histogram_along_axis_observable(self):
common.set_logging_level("warn")
fname = os.path.join(self.dir, "test_observables_hist_along_axis.h5")
simulation = Simulation()
simulation.set_kernel("SingleCPU")
box_size = common.Vec(10, 10, 10)
simulation.kbt = 2
simulation.periodic_boundary = [True, True, True]
simulation.box_size = box_size
simulation.register_particle_type("A", .2, 1.)
simulation.register_particle_type("B", .2, 1.)
simulation.register_potential_harmonic_repulsion("A", "B", 10)
simulation.add_particle("A", common.Vec(-2.5, 0, 0))
simulation.add_particle("B", common.Vec(0, 0, 0))
bin_borders = np.arange(0, 5, .01)
n_time_steps = 50
callback_hist = []
def hist_callback(hist):
callback_hist.append(hist)
handle = simulation.register_observable_histogram_along_axis(
2, bin_borders, 0, ["A", "B"], hist_callback)
with closing(
io.File(fname, io.FileAction.CREATE,
io.FileFlag.OVERWRITE)) as f:
handle.enable_write_to_file(f, u"hist_along_x_axis", int(3))
simulation.run(n_time_steps, 0.02)
handle.flush()
with h5py.File(fname, "r") as f2:
histogram = f2["readdy/observables/hist_along_x_axis/data"][:]
time_series = f2["readdy/observables/hist_along_x_axis/time"]
np.testing.assert_equal(time_series,
np.array(range(0, n_time_steps + 1))[::2])
for t in range(n_time_steps // 2):
np.testing.assert_equal(histogram[t],
np.array(callback_hist[t]))
def test_write_trajectory_as_observable(self):
traj_fname = os.path.join(self.dir, "traj_as_obs.h5")
simulation = Simulation("SingleCPU")
simulation.context.box_size = [5., 5., 5.]
simulation.context.particle_types.add("A", 0.0)
def callback(_):
simulation.add_particle("A", common.Vec(0, 0, 0))
simulation.register_observable_n_particles(1, ["A"], callback)
traj_handle = simulation.register_observable_trajectory(1)
with closing(io.File.create(traj_fname, io.FileFlag.OVERWRITE)) as f:
traj_handle.enable_write_to_file(f, u"", int(3))
simulation.run(20, 1)
r = TrajectoryReader(traj_fname)
trajectory_items = r[:]
for idx, items in enumerate(trajectory_items):
np.testing.assert_equal(len(items), idx+1)
for item in items:
np.testing.assert_equal(item.t, idx)
np.testing.assert_equal(item.position, np.array([.0, .0, .0]))
def test_radial_distribution_observable(self):
fname = os.path.join(self.dir, "test_observables_radial_distribution.h5")
simulation = Simulation()
simulation.set_kernel("SingleCPU")
box_size = common.Vec(10, 10, 10)
simulation.kbt = 2
simulation.periodic_boundary = [True, True, True]
simulation.box_size = box_size
simulation.register_particle_type("A", .2)
simulation.register_particle_type("B", .2)
simulation.register_potential_harmonic_repulsion("A", "B", 10, 2.)
simulation.add_particle("A", common.Vec(-2.5, 0, 0))
simulation.add_particle("B", common.Vec(0, 0, 0))
bin_borders = np.arange(0, 5, .01)
density = 1. / (box_size[0] * box_size[1] * box_size[2])
n_time_steps = 50
callback_centers = []
callback_rdf = []
def rdf_callback(pair):
callback_centers.append(pair[0])
callback_rdf.append(pair[1])
handle = simulation.register_observable_radial_distribution(1, bin_borders, ["A"], ["B"], density, rdf_callback)
with closing(io.File.create(fname)) as f:
handle.enable_write_to_file(f, u"radial_distribution", int(3))
simulation.run(n_time_steps, 0.02)
handle.flush()
with h5py.File(fname, "r") as f2:
bin_centers = f2["readdy/observables/radial_distribution/bin_centers"][:]
distribution = f2["readdy/observables/radial_distribution/distribution"][:]
for t in range(n_time_steps):
np.testing.assert_equal(bin_centers, np.array(callback_centers[t]))
np.testing.assert_equal(distribution[t], np.array(callback_rdf[t]))
def test_sanity(self):
sim = Simulation("SingleCPU")
sim.context.box_size = [10., 10., 10.]
np.testing.assert_equal(sim.kernel_supports_topologies(), True)
sim.context.topologies.add_type("TA")
sim.context.particle_types.add("T", 1.0, flavor=ParticleTypeFlavor.TOPOLOGY)
sim.context.topologies.configure_bond_potential("T", "T", BondedPotentialConfiguration(10., 11., "harmonic"))
particles = [sim.create_topology_particle("T", common.Vec(x, 0, 0)) for x in range(4)]
top = sim.add_topology("TA", particles)
graph = top.graph
graph.add_edge(0, 1)
graph.add_edge(1, 2)
graph.add_edge(2, 3)
np.testing.assert_equal(len(graph.get_vertices()), 4)
for v in graph.vertices:
if v.particle_index == 0:
np.testing.assert_equal(top.position_of_vertex(v), common.Vec(0, 0, 0))
np.testing.assert_equal(len(v.neighbors()), 1)
np.testing.assert_equal(1 in [vv.get().particle_index for vv in v], True)
if v.particle_index == 1:
np.testing.assert_equal(top.position_of_vertex(v), common.Vec(1, 0, 0))
np.testing.assert_equal(len(v.neighbors()), 2)
np.testing.assert_equal(0 in [vv.get().particle_index for vv in v], True)
np.testing.assert_equal(2 in [vv.get().particle_index for vv in v], True)
if v.particle_index == 2:
np.testing.assert_equal(top.position_of_vertex(v), common.Vec(2, 0, 0))
np.testing.assert_equal(len(v.neighbors()), 2)
np.testing.assert_equal(1 in [vv.get().particle_index for vv in v], True)
np.testing.assert_equal(3 in [vv.get().particle_index for vv in v], True)
if v.particle_index == 3:
np.testing.assert_equal(top.position_of_vertex(v), common.Vec(3, 0, 0))
np.testing.assert_equal(len(v.neighbors()), 1)
np.testing.assert_equal(2 in [vv.get().particle_index for vv in v], True)
top.configure()
sim.run(0, 1)
def test_center_of_mass_observable(self):
common.set_logging_level("warn")
fname = os.path.join(self.dir, "test_observables_com.h5")
simulation = Simulation()
simulation.set_kernel("SingleCPU")
box_size = common.Vec(10, 10, 10)
simulation.kbt = 2
simulation.periodic_boundary = [True, True, True]
simulation.box_size = box_size
simulation.register_particle_type("A", .2, 1.)
simulation.register_particle_type("B", .2, 1.)
simulation.add_particle("A", common.Vec(-2.5, 0, 0))
simulation.add_particle("B", common.Vec(0, 0, 0))
n_time_steps = 50
callback_com = []
def com_callback(vec):
callback_com.append(vec)
handle = simulation.register_observable_center_of_mass(
1, ["A", "B"], com_callback)
with closing(
io.File(fname, io.FileAction.CREATE,
io.FileFlag.OVERWRITE)) as f:
handle.enable_write_to_file(f, u"com", 3)
simulation.run(n_time_steps, 0.02)
handle.flush()
with h5py.File(fname, "r") as f2:
com = f2["readdy/observables/com/data"][:]
for t in range(n_time_steps):
np.testing.assert_equal(com[t]["x"], callback_com[t][0])
np.testing.assert_equal(com[t]["y"], callback_com[t][1])
np.testing.assert_equal(com[t]["z"], callback_com[t][2])
class TwoParticlesMiniExample(object):
def __init__(self):
KernelProvider.get().load_from_dir(platform_utils.get_readdy_plugin_dir())
self.simulation = Simulation()
self.simulation.set_kernel("CPU")
self.fig = plt.figure()
self.ax = self.fig.add_subplot(111, projection='3d')
plt.ioff()
self.fig.show()
self.prev_pos = {}
self.current_plot = None
self.T = 4000000
def ppos_callback(self, pos):
plt.cla()
self.ax.set_xlim([-1, 1])
self.ax.set_ylim([-1, 1])
self.ax.set_zlim([-1, 1])
r = [-.75, .75]
for s, e in combinations(np.array(list(product(r, r, r))), 2):
if np.sum(np.abs(s - e)) == r[1] - r[0]:
self.ax.plot3D(*zip(s, e), color="b")
pA = self.simulation.get_particle_positions("A")
pB = self.simulation.get_particle_positions("B")
if len(pA) == 1 and len(pB) == 1:
A = pA[0]; B = pB[0]
self.ax.scatter([A[0]], [A[1]], [A[2]], color="g", s=100)
self.ax.scatter([B[0]], [B[1]], [B[2]], color="r", s=100)
self.ax.plot3D([A[0], B[0]], [A[1], B[1]], [A[2], B[2]], color="r")
pC = self.simulation.get_particle_positions("C")
if len(pC) == 1:
C = pC[0]
self.ax.scatter([C[0]], [C[1]], [C[2]], color="b", s=100)
plt.pause(.001)
def start(self):
box_size = Vec(2.0, 2.0, 2.0)
depth = 2.
desired_dist = .25
force_constant = 4 * depth / (desired_dist * desired_dist)
no_interaction_dist = 1.5
self.simulation.kbt = 0.01
self.simulation.periodic_boundary = [False, False, False]
self.simulation.box_size = box_size
self.simulation.register_particle_type("A", .1, .1)
self.simulation.register_particle_type("B", .01, .1)
self.simulation.register_particle_type("C", .5, .1)
self.simulation.register_potential_piecewise_weak_interaction("A", "B", force_constant, desired_dist, depth,
no_interaction_dist) # (force constant, desired dist, depth, no interaction dist)
self.simulation.register_reaction_fusion("fusion", "A", "B", "C", 1000., .3, .5, .5)
self.simulation.register_reaction_fission("fission", "C", "A", "B", 1000., .25, .5, .5)
self.simulation.register_potential_box("A", 100., Vec(-.75, -.75, -.75), Vec(1.5, 1.5, 1.5), False)
self.simulation.register_potential_box("B", 100., Vec(-.75, -.75, -.75), Vec(1.5, 1.5, 1.5), False)
self.simulation.register_potential_box("C", 100., Vec(-.75, -.75, -.75), Vec(1.5, 1.5, 1.5), False)
self.simulation.add_particle("A", Vec(-.0, -.0, -.0))
self.simulation.add_particle("B", Vec(0.1, 0.1, 0.1))
self.simulation.register_observable_particle_positions(1, [], self.ppos_callback)
self.simulation.run(self.T, .0001)
n_calls += 1
if n_calls % 10000 == 0:
print("%s" % (10. * float(n_calls) / float(T)))
if __name__ == '__main__':
KernelProvider.get().load_from_dir(platform_utils.get_readdy_plugin_dir())
simulation = Simulation()
simulation.set_kernel("CPU")
box_size = Vec(10, 10, 10)
simulation.kbt = 2
simulation.periodic_boundary = [True, True, True]
simulation.box_size = box_size
simulation.register_particle_type("A", .2, 1.)
simulation.register_particle_type("B", .2, 1.)
simulation.register_potential_harmonic_repulsion("A", "B", 10)
simulation.add_particle("A", Vec(-2.5, 0, 0))
simulation.add_particle("B", Vec(0, 0, 0))
simulation.register_observable_radial_distribution(
10, np.arange(0, 5, .01), ["A"], ["B"],
1. / (box_size[0] * box_size[1] * box_size[2]), rdf_callback)
simulation.run(T, 0.02)
print("n_calls=%s" % n_calls)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(centers, rdf / n_calls)
plt.show()
class TwoParticlesMiniExample(object):
def __init__(self):
KernelProvider.get().load_from_dir(
platform_utils.get_readdy_plugin_dir())
self.simulation = Simulation()
self.simulation.set_kernel("CPU")
self.fig = plt.figure()
self.ax = self.fig.add_subplot(111, projection='3d')
plt.ioff()
self.fig.show()
self.prev_pos = {}
self.current_plot = None
self.T = 4000000
def ppos_callback(self, pos):
plt.cla()
self.ax.set_xlim([-1, 1])
self.ax.set_ylim([-1, 1])
self.ax.set_zlim([-1, 1])
r = [-.75, .75]
for s, e in combinations(np.array(list(product(r, r, r))), 2):
if np.sum(np.abs(s - e)) == r[1] - r[0]:
self.ax.plot3D(*zip(s, e), color="b")
pA = self.simulation.get_particle_positions("A")
pB = self.simulation.get_particle_positions("B")
if len(pA) == 1 and len(pB) == 1:
A = pA[0]
B = pB[0]
self.ax.scatter([A[0]], [A[1]], [A[2]], color="g", s=100)
self.ax.scatter([B[0]], [B[1]], [B[2]], color="r", s=100)
self.ax.plot3D([A[0], B[0]], [A[1], B[1]], [A[2], B[2]], color="r")
pC = self.simulation.get_particle_positions("C")
if len(pC) == 1:
C = pC[0]
self.ax.scatter([C[0]], [C[1]], [C[2]], color="b", s=100)
plt.pause(.001)
def start(self):
box_size = Vec(2.0, 2.0, 2.0)
depth = 2.
desired_dist = .25
force_constant = 4 * depth / (desired_dist * desired_dist)
no_interaction_dist = 1.5
self.simulation.kbt = 0.01
self.simulation.periodic_boundary = [False, False, False]
self.simulation.box_size = box_size
self.simulation.register_particle_type("A", .1, .1)
self.simulation.register_particle_type("B", .01, .1)
self.simulation.register_particle_type("C", .5, .1)
self.simulation.register_potential_piecewise_weak_interaction(
"A", "B", force_constant, desired_dist, depth, no_interaction_dist
) # (force constant, desired dist, depth, no interaction dist)
self.simulation.register_reaction_fusion("fusion", "A", "B", "C",
1000., .3, .5, .5)
self.simulation.register_reaction_fission("fission", "C", "A", "B",
1000., .25, .5, .5)
self.simulation.register_potential_box("A", 100.,
Vec(-.75, -.75, -.75),
Vec(1.5, 1.5, 1.5), False)
self.simulation.register_potential_box("B", 100.,
Vec(-.75, -.75, -.75),
Vec(1.5, 1.5, 1.5), False)
self.simulation.register_potential_box("C", 100.,
Vec(-.75, -.75, -.75),
Vec(1.5, 1.5, 1.5), False)
self.simulation.add_particle("A", Vec(-.0, -.0, -.0))
self.simulation.add_particle("B", Vec(0.1, 0.1, 0.1))
self.simulation.register_observable_particle_positions(
1, [], self.ppos_callback)
self.simulation.run(self.T, .0001)
def run(self):
###################################
#
# Units:
# - [t] = sec
#
###################################
tau = 1e-3
kernel_provider = KernelProvider.get()
kernel_provider.load_from_dir(platform_utils.get_readdy_plugin_dir())
simulation = Simulation()
simulation.set_kernel("CPU")
simulation.kbt = 1.0
simulation.box_size = Vec(3, 3, 3)
simulation.periodic_boundary = [True, True, True]
D = 1.0
R = .01
simulation.register_particle_type("A", D, R)
simulation.register_particle_type("2A", D, R)
simulation.register_particle_type("3A", D, R)
simulation.register_particle_type("B", D, R)
simulation.register_particle_type("GA", D, R)
simulation.register_particle_type("GB", D, R)
reaction_radius = .2
k1 = 4 * 1e-5
k2 = 50
k3 = 10
k4 = 250
V = simulation.box_size * simulation.box_size
N_GA = 100.0
N_GB = 1000.0
k_enzymatic = brentq(lambda x: erban_chapman(k1, 2, reaction_radius, x), 1e-10, 5000000000000)
k_enzymatic = 10. # k_enzymatic for reaction_radius = .1
print("k_enzymatic=%s" % k_enzymatic)
print("2 * k3 - k3 * k3 * tau = %s" % (2.0 * k3 - k3 * k3 * tau))
print("k3 * k3 * tau = %s" % (k3 * k3 * tau))
print("k_birthA = %s" % (k2 * V / N_GA))
print("k_birthB = %s" % (k4 * V / N_GB))
print("sqrt(R*R/D) = %s" % (np.sqrt(reaction_radius * reaction_radius / D)))
simulation.register_reaction_conversion("2A -> A", "2A", "A", 2.0 * k3 - k3 * k3 * tau)
simulation.register_reaction_decay("2A -> 0", "2A", k3 * k3 * tau)
simulation.register_reaction_fusion("A + A -> 2A", "A", "A", "2A", 1.0 / tau, reaction_radius, .5, .5)
simulation.register_reaction_enzymatic("2A + B -> 2A + A", "2A", "B", "A", k_enzymatic, reaction_radius)
simulation.register_reaction_fission("GA -> GA + A", "GA", "GA", "A", k2 * V / N_GA, reaction_radius, .5, .5)
simulation.register_reaction_decay("A -> 0", "A", k3)
simulation.register_reaction_fission("GB -> GB + B", "GB", "GB", "B", k4 * V / N_GB, reaction_radius, .5, .5)
simulation.add_particle("A", Vec(0, 0, 0))
ga_x = np.random.uniform(-0.5 * simulation.box_size[0], 0.5 * simulation.box_size[0], int(N_GA))
ga_y = np.random.uniform(-0.5 * simulation.box_size[1], 0.5 * simulation.box_size[1], int(N_GA))
ga_z = np.random.uniform(-0.5 * simulation.box_size[2], 0.5 * simulation.box_size[2], int(N_GA))
gb_x = np.random.uniform(-0.5 * simulation.box_size[0], 0.5 * simulation.box_size[0], int(N_GB))
gb_y = np.random.uniform(-0.5 * simulation.box_size[1], 0.5 * simulation.box_size[1], int(N_GB))
gb_z = np.random.uniform(-0.5 * simulation.box_size[2], 0.5 * simulation.box_size[2], int(N_GB))
for i in range(int(N_GA)):
simulation.add_particle("GA", Vec(ga_x[i], ga_y[i], ga_z[i]))
for i in range(int(N_GB)):
simulation.add_particle("GB", Vec(gb_x[i], gb_y[i], gb_z[i]))
N_B = 30000
boxsize = np.array([simulation.box_size[0], simulation.box_size[1], simulation.box_size[2]])
for i in range(N_B):
pos = np.random.random(3) * boxsize - 0.5 * boxsize
simulation.add_particle("B", Vec(pos[0], pos[1], pos[2]))
def callback(result):
n_a, n_b = result[0] + 2 * result[1] + 3 * result[2], result[3]
self._data[self._t, 0] = n_a
self._data[self._t, 1] = n_b
print("(%s,%s,a=%s,a2=%s,a3=%s)"%(n_a, n_b,result[0], result[1], result[2]))
self.lines.set_xdata(self._data[:self._t, 0])
self.lines.set_ydata(self._data[:self._t, 1])
self.ax.relim()
self.ax.autoscale_view()
#We need to draw *and* flush
self.fig.canvas.draw()
self.fig.canvas.flush_events()
plt.pause(.1)
self._t += 1
simulation.register_observable_n_particles_types(1, ["A", "2A", "3A", "B"], callback)
print("start run")
simulation.run(self._timesteps, tau)